气候变化领域集成服务门户(CCPortal): Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections

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DOI	10.5194/hess-24-2963-2020
	Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections
	Potter N.J.; Chiew F.H.S.; Charles S.P.; Fu G.; Zheng H.; Zhang L.
发表日期	2020
ISSN	1027-5606
起始页码	2963
结束页码	2979
卷号	24 期号:6
英文摘要	Dynamical downscaling of future projections of global climate model outputs can provide useful information about plausible and possible changes to water resource availability, for which there is increasing demand in regional water resource planning processes. By explicitly modelling climate processes within and across global climate model grid cells for a region, dynamical downscaling can provide higher-resolution hydroclimate projections and independent (from historical time series), physically plausible future rainfall time series for hydrological modelling applications. However, since rainfall is not typically constrained to observations by these methods, there is often a need for bias correction before use in hydrological modelling. Many bias-correction methods (such as scaling, empirical and distributional mapping) have been proposed in the literature, but methods that treat daily amounts only (and not sequencing) can result in residual biases in certain rainfall characteristics, which flow through to biases and problems with subsequently modelled runoff. We apply quantile-quantile mapping to rainfall dynamically downscaled by the NSW and ACT Regional Climate Modelling (NARCliM) Project in the state of Victoria, Australia, and examine the effect of this on (i) biases both before and after bias correction in different rainfall metrics, (ii) change signals in metrics in comparison to the bias and (iii) the effect of bias correction on wet-wet and dry-dry transition probabilities. After bias correction, persistence of wet states is under-correlated (i.e. more random than observations), and this results in a significant bias (underestimation) of runoff using hydrological models calibrated on historical data. A novel representation of quantile-quantile mapping is developed based on lag-one transition probabilities of dry and wet states, and we use this to explain residual biases in transition probabilities. Representing quantile-quantile mapping in this way demonstrates that any quantile mapping bias-correction method is unable to correct the underestimation of autocorrelation of rainfall sequencing, which suggests that new methods are needed to properly bias-correct dynamical downscaling rainfall outputs. © Author(s) 2020.
语种	英语
scopus关键词	Climate change; Electric power system interconnection; Hydrology; Mapping; Probability; Rain; Runoff; Time series; Bias-correction methods; Dynamical downscaling; Hydrological modelling; Rainfall characteristics; Regional climate modelling; Regional water resources; Resource availability; Transition probabilities; Climate models; autocorrelation; climate modeling; downscaling; future prospect; global climate; hydrological modeling; hydrometeorology; rainfall; runoff; water availability; water planning; Australia; Australian Capital Territory; New South Wales; Victoria [Australia]
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159379
作者单位	Potter, N.J., CSIRO Land and Water, Canberra, ACT 2601, Australia; Chiew, F.H.S., CSIRO Land and Water, Canberra, ACT 2601, Australia; Charles, S.P., CSIRO Land and Water, Floreat, WA 6148, Australia; Fu, G., CSIRO Land and Water, Floreat, WA 6148, Australia; Zheng, H., CSIRO Land and Water, Canberra, ACT 2601, Australia; Zhang, L., CSIRO Land and Water, Canberra, ACT 2601, Australia
推荐引用方式 GB/T 7714	Potter N.J.,Chiew F.H.S.,Charles S.P.,et al. Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections[J],2020,24(6).
APA	Potter N.J.,Chiew F.H.S.,Charles S.P.,Fu G.,Zheng H.,&Zhang L..(2020).Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections.Hydrology and Earth System Sciences,24(6).
MLA	Potter N.J.,et al."Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections".Hydrology and Earth System Sciences 24.6(2020).